DECISION SUPPORT FOR NEONATAL INTENSIVE CARE NURSING

长期目标是提高新生儿重症监护病房(NICU)为早产儿提供的护理质量和成本效益，为卫生保健从业者提供一个旨在加强他们实践的自动化知识系统。其目的是确定决策支持环境的核心特征，用于由临床环境中具有趋同和发散的价值观和主观决策概率的不同从业者护理的患者的一组不平凡的患者问题。这些活动的目的是开发一个原型决策支持系统，供新生儿护理从业者、S和新生儿重症监护室的新生儿专家使用。早产儿口服喂养准备情况的确定问题将为本研究提供初步的临床焦点。民族志和关键决策方法将被用来阐明从业者对早产儿口服喂养准备情况的主观估计是如何做出的。将使用内容分析来验证模型，并在适用的情况下向模型添加新的决策策略。不确定阶段将使用贝叶斯层次分析。将使用多属性效用技术(MAUT)进行偏好分析。一旦建立了决策模型，将由国家专家小组进行有效性测试。接下来，将建立一个原型决策支持系统(DSS)。决策模型和附带的决策支持系统将在最初的研究地点进行准确性、效率和用户接受度测试。决策模型和决策支持系统将在一些不同的医院进行现场推广测试。最后，对第二个临床问题使用该过程，不仅测试其与临床问题相关的概括性，而且还有助于确定决策建模过程的哪些元素可以推广到护理实践的其他领域。未来的目标将是比较使用传统技术的实践和使用结合到DSS中的决策分析模型扩大的实践，以辨别对患者结局和资源使用的影响。

The long term objective is to enhance the quality of care and cost-effectiveness of care provided to preterm infants in the neonatal intensive care unit (NICU) by providing health care practitioners with an automated knowledge-based system designed to augment their practice. The aim is to ascertain the core features of decision support environment for a nontrivial set of patient problems in patients cared for by a variety of practitioners with convergent and divergent values and subjective probabilities for decision making in a clinical setting. These activities are aimed at developing a prototype decision support system (DSS) for use by neonatal nurse practitioners (NNP)s and neonatologists in the NICU. The problem of determination of readiness for oral feeding in the preterm infant will provide the initial clinical focus for this research. Ethnography and the Critical Decision Method will be used to elucidate practitioners subjective estimates of how the determination of readiness for oral feedings in the preterm infant is made. A content analysis will be used to validate and, if applicable, to add new decision strategies to the model. Bayesian hierarchical analyses will be used for the uncertainty phase. A Multiattribute Utility Technique (MAUT) will be used to conduct preference analyses. Once the decision model has been structured, validity testing will be performed by a national panel of experts. Next, a prototype Decision Support System (DSS) system will be built. The decision-making model and the accompanying DSS will be tested for accuracy, efficiency and user acceptance at the initial research site. The decision-making model and DSS will be field tested for generalizability in a number of different hospitals. Finally, use of the process for a second clinical problem will be undertaken to test not only generalizability as it relates to a clinical problems, but also can help determine which elements of the decision modeling process can be generalized to other areas of nursing practice. A future goal will be to compare practice using traditional techniques and practice augmented using a decision-analytic model incorporated into a DSS to discern the effect on patient outcomes and resource use.